The overall objective of the proposed cross-disciplinary research is to use an integrated computational/experimental approach to study the acquisition and extinction of conditioned fear associations in the neural components of the fear circuit of mammals. We propose an interdependent series of experiments and biologically realistic simulations, using a 'from biology to model, to predictions, and back to biology'theme where experiments will constrain the design of the models ('from biology to model') and discrepancies between the models and expected outcomes will lead to the formulation of hypotheses ('to predictions') that will be tested experimentally ('back to biology'). The computational models will be developed using experimental data from laboratories of two neuroscience Co-PIs. Preliminary models, developed by our group over a period of 21/2 years demonstrate that they can provide significant insights into the intrinsic and synaptic mechanisms associated with learning and neuroplasticity in conditioned fear. The proposed research will expand this collaboration with the following specific aims: 1.To investigate the underlying mechanisms of learning and neuroplasticity in the amygdala related to the acquisition and extinction of conditioned fear using a biologically realistic computational model, and to test model predictions in experiments. From biology to model: Use published biology data (in vitro and in vivo), to investigate neurocomputational properties of single cell models of amygdala nuclei including lateral amygdala (LA), basal amygdala (BA), intercalated cells (ITC), and central nucleus (CeM and CeL). From biology to model and to predictions: Investigate how the key amygdala nuclei interact to acquire and extinguish conditioned fear memories using a biologically realistic network model that includes the single cell models. Make predictions to quantify the relative contributions of the various projections from LA to CeM, and about other mechanisms. From predictions to biology (and back): Assess the effects of fear conditioning and extinction on synaptic responses in the projections from LA to CeL, and CeL to CeM, in an in vitro slice preparation (to be performed in the Par[unreadable] lab). Incorporate findings from experiments and refine the model. 2. To investigate the mechanisms involved in the regulation of amygdala-dependent conditioning and extinction fear memory by the ventro medial prefrontal cortex, using a biologically realistic computational model, and to test model predictions in experiments. From biology to model: Use published biology data (in vitro and in vivo), to investigate the neurocomputational properties of single cells and networks in the pre-limbic (PL) and infra-limbic (IL) regions of the ventral medial prefrontal cortex (vmPFC). From biology to model and to predictions: Determine how the vmPFC regulates amygdala-dependent fear and extinction memories by developing an overall biologically realistic model including the vmPFC and the amygdala (from specific aim 1). Make predictions about the possible connections between vmPFC and the amygdala that may regulate these memories, and the effect of vmPFC inactivation on the tone responses of BA and Ce neurons. From predictions to biology (and back): Assess the effects of vmPFC inactivation on tone responses of BA and Ce neurons during fear conditioning and extinction (to be performed in Quirk lab). Incorporate findings from experiments and refine the model of vmPFC regulation of the amygdala in a single context. Intellectual Merit. The proposed interdisciplinary research will be the first to develop a biologically realistic computational model of the fear circuit. It will facilitate discovery of the learning and neuroplasticity mechanisms that underlie acquisition and extinction of conditioned fear in mammals, and will lead to valuable predictions, and novel directions for experimental research. The approach proposed will also lead to a better understanding of the systems and design principles governing the fear circuit. Broader Impact. The proposed computational model will provide new insights and understanding of a spectrum of psychiatric disorders including PTSD and anxiety disorders, which are thought to arise from deficits in the fear circuit. It will also be a key tool for the development of novel agents and strategies for the treatment of such disorders. Finally, the collaboration will also contribute to the generation of new curricula and materials for undergraduate, graduate and medical student education, and for K-12students.